Title:	Large-Scale Spatio-Temporal Reasoning and Learning
DNr:	Berzelius-2024-329
Project Type:	LiU Berzelius
Principal Investigator:	Fredrik Heintz <fredrik.heintz@liu.se>
Affiliation:	Linköpings universitet
Duration:	2024-09-01 – 2025-03-01
Classification:	10201
Homepage:	https://www.ida.liu.se/~frehe08/
Keywords:

Abstract

The goal of our research is to develop novel reasoning and learning methods for large-scale spatio-temporal applications. This includes for example large-language models, time-series learning (diffusion models and GANs) and multi-agent reinforcement learning. The expected scientific impact is publications in top-level conferences and the expected soecity impact is more effective decision-making methods for autonomous systems such as unmanned aircraft, more effective transporation solutions and methods for privacy-preserving synthetic data generation.